|Ethnicity classification based on fusion of face and gait|
|De Zhang; Yunhong Wang; Zhaoxiang Zhang; Maodi Hu
|会议名称||IEEE International Conference on Biometrics
|会议日期||March 29 – April 1 2012
|会议地点||New Delhi, India
|摘要||The recognition of ethnicity of an individual can be very useful in a video-based surveillance system. In this paper, we propose a multimodal biometric system involving an integration of frontal face and lateral gait, for the specific problem of ethnicity classification. This system performs a feature fusion to improve the discrimination of human ethnicity. Face features are extracted by means of the uniform LBP operator and gait information is characterized by a spatio-temporal representation. Afterwards, canonical correlation analysis (CCA), as a powerful tool to relate two sets of measurements, is used to fuse the two modalities at the feature level. A database including 36 walking people from East Asia and South America is built for the purpose of ethnicity classification. The experimental results show that the ethnicity recognition rate is improved by fusing face and gait information.|
Support Vector Machines
De Zhang,Yunhong Wang,Zhaoxiang Zhang,et al. Ethnicity classification based on fusion of face and gait[C],2012.